An improved combination of spectral and spatial features for vegetation classification in hyperspectral images

Remote Sensing

Volumn 9, Issue 3, 2017, Pages

  Fu, Yuanyuan ^a,b,c,d   Zhao, Chunjiang ^a,b,c,d   Wang, Jihua ^a   Jia, Xiuping ^e   Yang, Guijun ^a,b,c,d   Song, Xiaoyu ^a,b,c,d   Feng, Haikuan ^a,b,c,d  

^a INSTITUTE OF PLANT AND ENVIRONMENT PROTECTION   (China)

^b NATIONAL ENGINEERING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

^c AGRO ENVIRONMENTAL PROTECTION INSTITUTE   (China)

^d Beijing Engineering Research Center of Agricultural Internet of Things   (China)

^e UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Feature selection; Gabor features; Hyperspectral image; Scatter matrix based class separability; Vegetation classification

Indexed keywords

AGRICULTURAL MACHINERY; AGRICULTURE; FEATURE EXTRACTION; HYPERSPECTRAL IMAGING; IMAGE CLASSIFICATION; IMAGE RETRIEVAL; INDEPENDENT COMPONENT ANALYSIS; SPECTROSCOPY; VEGETATION;

CLASS SEPARABILITY; CLASS SEPARABILITY MEASURE; COMPARATIVE EXPERIMENTS; DISCRIMINATIVE FEATURES; FEATURE SELECTION METHODS; GABOR FEATURE; SUPPORT VECTOR MACHINE CLASSIFIERS; VEGETATION CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 85019393092     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9030261     Document Type: Article

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